A French Non-Native Corpus for Automatic Speech Recognition

Tien-Ping Tan, Laurent Besacier


Abstract
Automatic speech recognition (ASR) technology has achieved a level of maturity, where it is already practical to be used by novice users. However, most non-native speakers are still not comfortable with services including ASR systems, because of the accuracy on non-native speakers. This paper describes our approach in constructing a non-native corpus particularly in French for testing and adapting non-native speaker for automatic speech recognition. Finally, we also propose in this paper a method for detecting pronunciation variants and possible pronunciation mistakes by non-native speakers.
Anthology ID:
L06-1012
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Editors:
Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/33_pdf.pdf
DOI:
Bibkey:
Cite (ACL):
Tien-Ping Tan and Laurent Besacier. 2006. A French Non-Native Corpus for Automatic Speech Recognition. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
Cite (Informal):
A French Non-Native Corpus for Automatic Speech Recognition (Tan & Besacier, LREC 2006)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/33_pdf.pdf